Introduction to Algorithms
Efficient Data Allocation over Multiple Channels at Broadcast Servers
IEEE Transactions on Computers
Broadcast data allocation for efficient access of multiple data items in mobile environments
Mobile Networks and Applications
A linearly convergent method for broadcast data allocation
Computers & Mathematics with Applications
Information Sciences: an International Journal
On-demand broadcast for multiple-item requests in a multiple-channel environment
Information Sciences: an International Journal
A branch-and-cut algorithm for the minimum labeling Hamiltonian cycle problem and two variants
Computers and Operations Research
A novel hash-based streaming scheme for energy efficient full-text search in wireless data broadcast
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications - Volume Part I
Computer Networks: The International Journal of Computer and Telecommunications Networking
Information Sciences: an International Journal
Utility driven optimization of real time data broadcast schedules
Applied Soft Computing
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In wireless environments, many mobile users may raise queries for accessing multiple data items, e.g., stock information or traffic condition, simultaneously. Most queries are identical. That is, many users may have an interest in some popular data items. Because data broadcast can offer unlimited users shareable information at the same time, a broadcast server is usually employed to disseminate all the data items periodically. Intuitively, popular data items should be scheduled and transmitted to users more efficiently than ordinary ones, so these users can thus save access time. To improve customer satisfaction, the author considers a broadcast program scheduling problem in such an environment and aims to minimize mobile users' worst access time as well as their battery power consumption by generating near-optimal broadcast programs. The author provides theoretical analysis as a foundation of mapping the problem to another domain i.e., from unit item to unit fragment and this transformation makes the problem easy to solve. Moreover, an ON logN algorithm is proposed for this NP-hard problem. Finally, experimental results show that access time can be reduced by carefully scheduling broadcast programs. It suggests that other similar optimization problems can be solved similarly.